The results of MSA + MSA2 are usually quite good, but a quick check
is recommended to avoid spending time on instance segmentation of poor
point clouds. The checks are two-fold:
i) Analysis of the MSA2
report
ii) Visual inspection of plot stems cross-section
1. MSA2 report
The results from MSA 2 are
usually accurate, but occasionally individual scans might be poorly
co-registered. The starting point for identifying these scans is the
‘full report’ generated by MSA 2 module. These scans can then be viewed
in 3D, and the operator can decide whether they should be included or
excluded.
i) Open the corresponding MSA 2 report and review
section 4.4.2: Plane Patches. What you are looking for are substantial
spikes in the residuals of distance. Typically when std(mad) > 0.0015
m. The first figure below is approximately normal. The second shows a
spike in ScanPos146, that requires investigation.
ii) Visualise the scan
in question, and neighbouring scans (e.g., in the above example,
143-150), and colour them by unique values. Switch view type → Switch to
Single color mode. You are trying to identify if the scan position is
poorly registered. This can perhaps most readily be found by looking at
crosssections of the point cloud (e.g., using the Height Filter).
Particularly focus on the stems and low-order branches, checking to see
if there is any duplication of ghosting of surfaces. It can be difficult
to distinguish between co-registration errors and effects from wind for
high-order branches higher up in the canopy.
iii) If a scan is
considered poorly-registered by the operator, then it should be excluded
from the project: R-click ScanPosXXX → Unregister (this is not
the same as toggling the ‘registered’ flag)
2.
Visual inspection of plot stems cross-section
i) Make an
octree pointcloud including all the scans. Typically, we downsample to
1cm for this with the following settings in the One-Touch Processing
Wizard:
ii)
Now we will calculate the height above terrain for each point (this is
different than the Z-value).
Right click on the created octree
point cloud → LIS Tree Analyzer Tools → Ground Classifier
Select the option that best matche the terrain of the plot:
iii) Visualise the octree
point cloud and us the “Point attribute filter” to display a cross
section, using “LIS Height Above Ground” as a visual filter. Typically
you would take a slice of 0.3m, eg 1-1.3m above terrein. Drag in the
locations of the ScanPos too:
iv) Zoom in closer and navigate through the
whole plot, visually looking for indications of mis-registration. The
easiest is to follow the ScanPos order
v) Finally, we will inspect a vertical cross
section of the plot. Disable the point attribute filter “LIS Height
Above Ground” and initiate the filter on x (XYZ[0]) or y (XYZ[1]). In
this example we display a 5m transect using a filter on the x-coordinate